A Structural Support Vector Method for Extracting Contexts and Answers of Questions from Online Forums

This paper addresses the issue of extracting contexts and answers of questions from post discussion of online forums. We propose a novel and unified model by customizing the structural Support Vector Machine method. Our customization has several attractive properties: (1) it gives a comprehensive graphical representation of thread discussion. (2) It designs special inference algorithms instead of generalpurpose ones. (3) It can be readily extended to different task preferences by varying loss functions. Experimental results on a real data set show that our methods are both promising and flexible.

• Type: Journal
• Year: 2009
• Where: EMNLP
• Authors: Wen-Yun Yang, Yunbo Cao, Chin-Yew Lin
• Keywords: Comprehensive Graphical Representation, EMNLP 2009, Natural Language Processing, Special Inference Algorithms, Structural Support Vector